Method and system for determining degradation in performance of an electronic device connected to a communication network

ABSTRACT

A method for determining degradation in performance of an electronic device connected to a communication network for an aerial vehicle includes monitoring, by one or more computing device(s), communications on the communication network during a validation period. The method further includes generating, by the computing device(s), a baseline operating profile of the electronic device based, at least in part, on the communications monitored during the validation period. In addition, the method includes monitoring, by the computing device(s), communications on the communication network during a post-validation period. The method further includes determining, by the computing device(s), a present operating profile of the electronic device based, at least in part, on the communications monitored during the post-validation period. In addition, the method includes determining, by the computing device(s), degradation in performance of the electronic device when the present operating profile deviates from the baseline operating profile.

FIELD

The present subject matter relates generally to a method and system formonitoring operation of an electronic device connected to acommunication network for an aerial vehicle.

BACKGROUND

Deterministic networks attempt to control when a data packet arrives atits destination (e.g., within a bounded timeframe). This category ofnetworking can be used for a myriad of applications such as industrialautomation, vehicle control systems, and other systems that require theprecise delivery of control commands to a controlled device. Inparticular, a protocol can define communications between electronicdevices connected to a communication network used in aviation,automotive and industrial control applications. For example, theprotocol may permit a first electronic device on the communicationnetwork to communicate with a second electronic device on thecommunication network. However, the protocol may preclude the firstelectronic device from communicating with a third electronic device onthe communication network. In addition, the protocol may define thecontent of messages exchanged between the first electronic device andthe second electronic device. In this way, communications on the networkcan be deterministic.

BRIEF DESCRIPTION

Deterministic networks attempt to control when a data packet arrives atits destination (e.g., within a bounded timeframe). This category ofnetworking can be used for a myriad of applications such as industrialautomation, vehicle control systems, and other systems that require theprecise delivery of control commands to a controlled device.

Aspects and advantages of the present disclosure will be set forth inpart in the following description, or may be obvious from thedescription, or may be learned through practice of the presentdisclosure.

In one example embodiment, a method for determining degradation inperformance of an electronic device connected to a communication networkfor an aerial vehicle includes monitoring, by one or more computingdevice(s), communications on the communication network during avalidation period. The method further includes generating, by thecomputing device(s), a baseline operating profile of the electronicdevice based, at least in part, on the communications monitored duringthe validation period. In addition, the method includes monitoring, bythe computing device(s), communications on the communication networkduring a post-validation period. The method further includesdetermining, by the computing device(s), a present operating profile ofthe electronic device based, at least in part, on the communicationsmonitored during the post-validation period. In addition, the methodincludes determining, by the computing device(s), degradation inperformance of the electronic device when the present operating profiledeviates from the baseline operating profile. The method furtherincludes generating, by the computing device(s), a notificationindicating the degradation in the performance of the electronic device.

In another example embodiment, a system for determining degradation inperformance of an electronic device connected to a communication networkfor an aerial vehicle includes one or more computing device(s) connectedto the communication network. The computing device(s) include one ormore processor(s) and one or more memory device(s) storing instructionsthat can be executed by the one or more computing device(s) to performoperations. The computing device(s) can be configured to monitorcommunications on the communication network during a validation period.In addition, the computing device(s) can be configured to generate abaseline operating profile of the electronic device based, at least inpart, on the communications monitored during the validation period. Thecomputing device(s) can also be configured to monitor communications onthe communication network during a post-validation period. In addition,the computing device(s) can generate a present operating profile of theelectronic device based, at least in part, on the communicationsmonitored during the post-validation period. The computing device(s) canbe configured to determine degradation in performance of the electronicdevice when the present operating profile deviates from the baselineoperating profile. In addition, the computing device(s) canautomatically schedule the aerial vehicle for maintenance when thepresent operating profile deviates from the baseline operating profile.

These and other features, aspects and advantages of the presentdisclosure will become better understood with reference to the followingdescription and appended claims. The accompanying drawings, which areincorporated in and constitute a part of this specification, illustrateembodiments of the present disclosure and, together with thedescription, serve to explain the principles of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

A full and enabling disclosure of the present disclosure, including thebest mode thereof, directed to one of ordinary skill in the art, is setforth in the specification, which makes reference to the appended Figs.,in which:

FIG. 1 illustrates an aerial vehicle according to example embodiments ofthe present disclosure;

FIG. 2 illustrates a computing system for an aerial vehicle according toexample embodiments of the present disclosure;

FIG. 3 illustrates an flight management system for an aerial vehicleaccording to example embodiments of the present disclosure;

FIG. 4 illustrates an example system for determining degradation inperformance of an electronic device connected to a communication networkfor an aerial vehicle;

FIG. 5 illustrates a computing device according to example embodimentsof the present disclosure;

FIG. 6 illustrates a baseline profile for the electronic device of FIG.4 according to example embodiments of the present disclosure;

FIG. 7 illustrates a present operating profile for the electronic deviceof FIG. 4 according to example embodiments of the present disclosure;

FIG. 8 illustrates another example system for monitoring operation of anelectronic device communicatively coupled to a communication network foran aerial vehicle according to example embodiments of the presentdisclosure; and

FIG. 9 illustrates a flow diagram of an example method for determiningdegradation in performance of an electronic device connected to acommunication network for an aerial vehicle.

DETAILED DESCRIPTION

Reference will now be made in detail to present embodiments of thepresent disclosure, one or more examples of which are illustrated in theaccompanying drawings. The detailed description uses numerical andletter designations to refer to features in the drawings.

As used herein, the terms “first” and “second” can be usedinterchangeably to distinguish one component from another and are notintended to signify location or importance of the individual components.The singular forms “a”, “an”, and “the” include plural references unlessthe context clearly dictates otherwise.

Example embodiments of the present disclosure are directed to systemsand methods for detecting degradation in performance of an electronicdevice connected to a communication network for an aerial vehicle. Inone example embodiment, one or more computing devices connected to thecommunication network can monitor communications on the communicationnetwork during both a validation period and a post-validation period.The validation period can include a period of time during whichoperation of the electronic can be validated. In particular, thevalidation period can span one or more test-flights of the aerialvehicle. In contrast, the post-validation period can include a period oftime following the validation period. However, similar to the validationperiod, the post-validation period can also span one or more flights ofaerial vehicle. In addition, the one or more test-flights and the one ormore flights can each include a plurality of flight phases.

In example embodiments, the one or more computing devices can generate abaseline operating profile of the electronic device. More specifically,the one or more computing devices can generate the baseline operatingprofile based, at least in part, on communications monitored during thevalidation period. In example embodiments, the baseline operatingprofile can include a first plurality of values. In particular, eachvalue of the first plurality of values can indicate a baseline responsetime of the electronic device during one flight phase of thetest-flight(s). In addition, the baseline operating profile can includeone or more environmental parameters affecting operation of theelectronic device. The one or more environmental parameters can includean operating temperature of the electronic device, a vibrationmeasurement indicating vibration of the electronic device, a humiditymeasurement indicating humidity of an environment in which theelectronic device is operating, an altitude measurement, and an amountof traffic on the communication network.

The one or more computing devices can also generate a present operatingprofile of the electronic device. More specifically, the one or morecomputing devices can generate the present operating profile during thepost-validation period. In example embodiments, the present operatingprofile can include a second plurality of values. In particular, eachvalue of the second plurality of values can indicate a present responsetime of the electronic device during one flight phase of the flight(s).

The one or more computing devices can determine degradation in theperformance of the electronic device when the present operating profiledeviates from the baseline operating profile. In this way, degradationin the performance of the electronic device can be determined withoutusing additional sensors in the device. Additionally, the one or morecomputing devices can transmit the present operating profile of theelectronic device to a remote computing system configured to estimate anamount of time remaining before the electronic device become inoperable(that is, the electronic device can no longer perform its primaryfunctions). In example embodiments, the remote computing device caninclude a model that is trained, at least in part, on an operatingprofile of one or more electronic devices that are identical toelectronic device and connected to a communication network for anotheraerial vehicle. The model can learn how the one or more environmentalparameters can affect a lifespan of the one or more electronic devices.As such, the model can estimate an amount of time remaining before theelectronic device becomes inoperable.

The systems and methods described herein can provide a number oftechnical effects and benefits. For instance, if the aerial vehicle isone of a plurality of aerial vehicles owned by an airliner, estimatingthe amount of time before the electronic device becomes inoperable canallow the airliner to schedule maintenance on the aerial vehicle at atime that minimizes economic losses. More specifically, the airliner canschedule maintenance at a time when the aerial vehicle is not needed.

FIG. 1 depicts an aerial vehicle 100 according to example embodiments ofthe present disclosure. As shown, the aerial vehicle 100 can include afuselage 120, one or more engine(s) 130, and a cockpit 140. In exampleembodiments, the cockpit 140 can include a flight deck 142 havingvarious instruments 144 and flight displays 146. It should beappreciated that instruments 144 can include, without limitation, adial, gauge, or any other suitable analog device.

A first user (e.g., a pilot) can be present in a seat 148 and a seconduser (e.g., a co-pilot) can be present in a seat 150. The flight deck142 can be located in front of the pilot and co-pilot and may providethe flight crew (e.g., pilot and co-pilot) with information to aid inoperating the aerial vehicle 100. The flight displays 146 can includeprimary flight displays (PFDs), multi-function displays (MFDs), or both.During operation of the aerial vehicle 100, both the instruments 144 andflight displays 146 can display a wide range of vehicle, flight,navigation, and other information used in the operation and control ofthe aerial vehicle 100.

The instruments 144 and flight displays 146 may be laid out in anymanner including having fewer or more instruments or displays. Further,the flight displays 146 need not be coplanar and need not be the samesize. A touch screen display or touch screen surface (not shown) may beincluded in the flight displays 146 and may be used by one or moreflight crew members, including the pilot and co-pilot, to interact withthe aerial vehicle 100. The touch screen surface may take any suitableform including that of a liquid crystal display (LCD) and may usevarious physical or electrical attributes to sense inputs from theflight crew. It is contemplated that the flight displays 146 can bedynamic and that one or more cursor control devices (not shown) and/orone or more multifunction keyboards 152 can be included in the cockpit140 and may be used by one or more flight crew members to interact withsystems of the aerial vehicle 100. In this manner, the flight deck 142may be considered a user interface between the flight crew and theaerial vehicle 100.

Additionally, the cockpit 140 can include an operator manipulated inputdevice 160 that allow members of the flight crew to control operation ofthe aerial vehicle 100. In one example embodiment, the operatormanipulated input device 160 can be used to control the engine power ofthe one or more engines 130. More specifically, the operator manipulatedinput device 160 can include a lever having a handle, and the lever canbe movable between a first position and a second position. As such, aflight crew member can move the lever between the first and secondpositions to control the engine power of the one or more engine(s) 130.

The numbers, locations, and/or orientations of the components of exampleaerial vehicle 100 are for purposes of illustration and discussion andare not intended to be limiting. As such, those of ordinary skill in theart, using the disclosures provided herein, shall understand that thenumbers, locations, and/or orientations of the components of the aerialvehicle 100 can be adjusted without deviating from the scope of thepresent disclosure.

Referring now to FIG. 2, the aerial vehicle 100 can include an onboardcomputing system 210. As shown, the onboard computing system 210 caninclude one or more onboard computing device(s) 220 that can beassociated with, for instance, an avionics system. In exampleembodiments, one or more of the onboard computing device(s) 220 caninclude a flight management system (FMS).

Alternatively or additionally, the one or more onboard computingdevice(s) 220 can be coupled to a variety of systems on the aerialvehicle 100 over a communication network 230.

The communication network 230 can include, for example, a local areanetwork (LAN), a wide area network (WAN), SATCOM network, VHF network, aHF network, a Wi-fi network, a WiMAX network, a gatelink network and/orany other suitable communication network for transmitting message to andfrom the aerial vehicle 100. The communication network 230 can alsoinclude a data bus or combination of wired and/or wireless communicationlinks. Such networking environments are commonplace in computernetworks, intranets and the internet and may use a wide variety ofdifferent communication protocols. It will be appreciated that suchnetwork computing environments will typically encompass many types ofcomputer system configuration, including personal computers, hand-helddevices, multiprocessor systems, microprocessor-based or programmableconsumer electronics, network PCs, minicomputers, mainframe computers,and the like. Moreover, the communication network 230 can include one ormore communication lines 232 that can communicatively couple the variousdevices and/or systems onboard the aircraft 200. In example embodiments,the communication lines 232 of the communication network 230 can includea data bus or a combination of wired and/or wireless communicationlinks. It should be appreciated that the communication lines 232 can bebased on ARINC 429, MIL-STD 1553, IEEE 802.3, ARINC 825, Time TriggeredEthernet/SAE AS6802or any other suitable standard.

In example embodiments, the onboard computing device(s) 220 can be incommunication with a display system 240, such as the flight displays 146(FIG. 1) of the aerial vehicle 100. More specifically, the displaysystem 240 can include one or more display device(s) that can beconfigured to display or otherwise provide information generated orreceived by the onboard computing system 210. In example embodiments,information generated or received by the onboard computing system 210can be displayed on the one or more display device(s) for viewing byflight crew members of the aerial vehicle 102. The display system 225can include a primary flight display, a multipurpose control displayunit, or other suitable flight displays commonly included within thecockpit 140 (FIG. 1) of the aerial vehicle 100.

The onboard computing device(s) 220 can also be in communication with aflight management computer 250. In example embodiments, the flightmanagement computer 250 can automate the tasks of piloting and trackingthe flight plan of the aerial vehicle 100. It should be appreciated thatthe flight management computer 250 can include or be associated with anysuitable number of individual microprocessors, power supplies, storagedevices, interface cards, auto flight systems, flight managementcomputers, the flight management system (FMS) and other standardcomponents. The flight management computer 250 can include or cooperatewith any number of software programs (e.g., flight management programs)or instructions designed to carry out the various methods, processtasks, calculations, and control/display functions necessary foroperation of the aerial vehicle 100. The flight management computer 250is illustrated as being separate from the onboard computing device(s)220. However, those of ordinary skill in the art, using the disclosuresprovided herein, will understand that the flight management computer 250can also be included with or implemented by the onboard computingdevice(s) 220.

The onboard computing device(s) 220 can also be in communication withone or more aerial vehicle control system(s) 260. The aerial vehiclecontrol system(s) 260 can be configured to perform various aerialvehicle operations and control various settings and parametersassociated with the aerial vehicle 100. For instance, the aerial vehiclecontrol system(s) 320 can be associated with one or more engine(s) 130and/or other components of the aerial vehicle 100. The aerial vehiclecontrol system(s) 260 can include, for instance, digital controlsystems, throttle systems, inertial reference systems, flight instrumentsystems, engine control systems, auxiliary power systems, fuelmonitoring systems, engine vibration monitoring systems, communicationssystems, flap control systems, flight data acquisition systems, a flightmanagement system (FMS), and other systems.

Referring now to FIG. 3, the aerial vehicle 100 can include a flightmanagement system 300 (FMS). The FMS 300 can provide flight planning andnavigation capability and may be communicatively coupled with otheravionics and aircraft systems as well, such as e.g., a globalpositioning system (GPS), VHF omnidirectional range/distance measuringequipment (VOR/DME), Inertial Reference/Navigation Systems (IRS/INS),flight controls, etc. As will be discussed below in more detail, the FMS300 can include a control display unit (CDU) or multi-purpose controldisplay unit (MCDU), and various databases, such as e.g., a navigationdatabase (NDB) and an engine/aerial vehicle performance database.

In example embodiments, the FMS 300 can include a control display unit(CDU) 310 having a display 312 and one or more input devices 314 (e.g.,keyboard). The one or more input devices 314 can be used to gather inputdata from the flight crew. The display 312 can present output data, suchas a flight plan for the aerial vehicle 100. The CDU can include one ormore processor(s) and one or more memory device(s). The one or morememory device(s) can store instructions that when executed by the one ormore processor(s) cause the one or more processor(s) to perform theoperations and functions, such as e.g., flight planning tasks. In thisway, the CDU can interpret incoming data and automatically adjust theoutput data (e.g., flight plan) while the aerial vehicle 100 isairborne.

The FMS 300 can also include a navigation database 320 communicativelycoupled to the flight management computer 250. In example embodiments,the navigation database 320 contains information stored on a memorydevice that allows the flight management computer 250 to generate aflight plan and update the flight plan as needed when the aerial vehicle100 is airborne. In particular, the information stored in the navigationdatabase 320 can include, without limitation, airways and associatedwaypoints. An airway can be a predefined path that connects onespecified location (e.g., departing airport) to another specifiedlocation (e.g., destination airport). In addition, a waypoint caninclude one or more intermediate point(s) or place(s) on the predefinedpath defining the airway.

The FMS 300 can also include a performance database 330 communicativelycoupled to the flight management computer 250. In example embodiments,the performance database 330 contains information stored on a memorydevice that allows the flight management computer 250 to compute optimalfuel burn and other performance-based indicators so that the flight plancan be adjusted in favor of a more efficient flight path. It should beappreciated that the navigation database 320 and the performancedatabase 330 can be stored on the same memory device or on separate,dedicated devices. It should also be appreciated that the memory devicescan be electrically erasable programmable read-only memory (EEPROM)cards communicatively coupled to the flight management computer 250.

FIG. 4 depicts an example embodiment of a system 400 for determiningdegradation in performance of one or more electronic device(s) 410connected to the communication network 230 for the aerial vehicle 100.More specifically, the electronic device(s) 410 can be connected to thecommunication network 230 via the one or more communication lines 232.In an example embodiment, the electronic device 410 can be the flightmanagement computer 250 (FIG. 3) of the FMS 300. In another exampleembodiment, the electronic device 410 can be an electronic actuatorconfigured to control operation of a landing gear assembly (not shown)for the aerial vehicle 100. In yet another example embodiment, theelectronic device 410 can be a flight control, such as the operatormanipulated input device 160 discussed above with reference to FIG. 1.It should be appreciated, however, that the electronic device 410 can beany suitable electronic device that is communicatively coupled to thecommunication network 230.

Referring now to FIGS. 4 and 5 in combination, the system 400 caninclude one or more computing device(s) 420 communicatively coupled tothe communication network 230. More specifically, the computingdevice(s) 420 can be communicatively coupled to the communicationnetwork 230 via the one or more communication lines 232. In alternativeembodiments, however, the computing device(s) 420 can be communicativelycoupled to the network 230 via a network switch. More specifically, thenetwork switch can be connected to the communication lines 232 and thecomputing device(s) 420. In this way, communications (e.g., datapackets) on the communication lines 232 can be routed to the computingdevice(s) 420 by way of the network switch.

As shown, the computing device(s) 420 can include one or moreprocessor(s) 422 and one or more memory device(s) 424. The processor(s)422 can include any suitable processing device, such as amicroprocessor, microcontroller, integrated circuit, logic device, orother suitable processing device. The memory device(s) 424 can includeone or more computer-readable media, including, but not limited to,non-transitory computer-readable media, RAM, ROM, hard drives, flashdrives, or other memory devices.

The memory device(s) 424 can store information accessible by theprocessor(s) 422, including computer-readable instructions 426 that canbe executed by the processor(s) 422. The computer-readable instructions426 can be any set of instructions that when executed by theprocessor(s) 422, cause the processor(s) 422 to perform operations. Thecomputer-readable instructions 426 can be software written in anysuitable programming language or can be implemented in hardware. In someembodiments, the computer-readable instructions 426 can be executed bythe processor(s) 422 to cause the processor(s) 422 to performoperations, such as monitor operation of the electronic device 410, asdescribed below with reference to FIG. 9.

The memory device(s) 424 can further store data 428 that can be accessedby the processor(s) 422. For example, the data 428 can include any dataused for determining degradation in the performance of the electronicdevice 410, as described herein. The data 428 can include one or moretable(s), function(s), algorithm(s), model(s), equation(s), etc. fordetermining degradation in the performance of the electronic device 410according to example embodiments of the present disclosure.

The computing device(s) 420 can also include a communication interface430 used to communicate, for example, with the communication network230. The communication interface 430 can include any suitable componentsfor interfacing with the communication network 230, including forexample, transmitters, receivers, ports, controllers, antennas, or othersuitable components.

In example embodiments, the computing device(s) 420 can monitorcommunications patterns between two or more electronic device(s)connected to the communication network 230. More specifically, thecomputing device(s) 420 can monitor the communication patterns during avalidation period that includes a period of time during which operationof the electronic device 410 can be validated. In example embodiments,the period of time can span one or more test-flight(s) of the aerialvehicle 100. The test-flight(s) can include a plurality of flight phasesindicative of operation of the aerial vehicle 100. The plurality offlight phases can include, without limitation, a standing at gate phase,a taxiing phase, a takeoff phase, a climb phase, a cruise phase, anapproach phase and a landing phase.

When the computing device(s) 420 monitor communication patterns duringthe validation period, the computing device(s) 420 can determine howfrequently two electronic device(s) communicate with one another duringeach phase of the plurality of flight phases. As an example, thecomputing device(s) 420 can monitor communications between a firstelectronic device on the network 230 and a second electronic device onthe network 230. More specifically, the computing device(s) 420 candetermine the first electronic device communicates with the secondelectronic device every five seconds during the takeoff phase of thetest-flight(s). In contrast, the computing device(s) 420 can determinethe first electronic device does not communicate with the secondelectronic device during the cruise phase of the test-flight(s). In thisway, the computing device(s) 420 can determine how frequently the firstelectronic device and the second electronic device communicate with oneanother during at least the takeoff and cruise phases of thetest-flight(s). It should be appreciated, however, that the computingdevice(s) can determine how frequently two devices communicate with oneanother during any suitable phase of the test-flight(s).

Alternatively or additionally, the computing device(s) 420 can monitorthe content of communications between the first electronic device andthe second electronic device. More specifically, the computing device(s)420 can monitor one or more parameter(s) included in a first data packetoriginating from the first electronic device. In addition, the computingdevice(s) 420 can monitor the parameter(s) included in a second datapacket originating from the second electronic device and responsive tothe first data packet. In example embodiments, the parameter(s) caninclude, without limitation, data included in a payload section of thesecond data packet. As will be discussed below in more detail, thecommunication patterns monitored during the validation period can beused by the computing device(s) 420 to generate a baseline operatingprofile 600 of the electronic device 410.

Referring now to FIGS. 4 through 6 in combination, the baselineoperating profile 600 can be indicative of operation of the electronicdevice 410 during the validation period. As shown, the baselineoperating profile 600 can include a baseline response time of theelectronic device 410. In particular, the baseline response time canindicate an amount of time the electronic device 410 takes to respond toa communication originating from another node (e.g., electronic device)of the communication network 230. As an example, the computing device(s)420 can listen for transmission of a first data packet intended for theelectronic device 410. In particular, the first data packet canoriginate from another electronic device connected to the communicationnetwork 230. The computing device(s) 420 can also listen fortransmission of a second data packet originating from the electronicdevice 410 and responsive to the first data packet. The computingdevice(s) 420 can be configured to determine a time lapse fromtransmission of the first data packet to transmission of the second datapacket. In this way, the computing device(s) 420 can determine abaseline response time of the electronic device 410.

In example embodiments, the baseline operating profile 600 can include afirst plurality of values 610 for the baseline response time of theelectronic device 410, and each value of the first plurality of values610 can indicate the baseline response time during one of the flightphases. For example, a first value 612 can indicate the baselineresponse time of the electronic device 410 during the takeoff phase ofthe test-flight(s), whereas a second value 614 can indicate the baselineresponse time of the electronic device 410 during the climb phase. Aswill be discussed, a tolerance (not shown) can be assigned to each valueof the first plurality of values 610 and can be included in the baselineoperating profile 600.

In example embodiments, the tolerance can be determined by amanufacturer of the electronic device 410. In addition, the tolerancecan include an upper bound and a lower bound for the response time ofthe electronic device 410. In this way, the upper bound and the lowerbound can define a window of time in which the electronic device 410must transmit a response (e.g., data packet) to a command (e.g., datapacket) received from another electronic device on the network 230. Thewindow of time defined by the upper and lower bounds can vary amongstthe plurality of flight phases. For example, the window of time duringthe takeoff phase can be greater than the window of time during thecruise phase. As will be discussed below in more detail, one or moreenvironmental parameter(s) affecting operation of the electronic device410 can also be included in the baseline operating profile 600.

The environmental parameter(s) can include an operating temperature T ofthe electronic device 410. In example embodiments, a temperature sensor440 can be configured to sense the operating temperature T of theelectronic device 410. In addition, the temperature sensor 440 can becommunicatively coupled to the communication network 230. In exampleembodiments, the computing device(s) 420 can transmit a first signal S₁to the temperature sensor 440. After receiving the first signal S₁, theelectronic device 410 can transmit a second signal S2 to the computingdevice(s) 420 via the communication network 230. More specifically, thesecond signal S2 can include data indicative of the operatingtemperature T of the electronic device 410.

The operating temperature T of the electronic device 410 can varyamongst the plurality of flight phases of the test-flight(s). As such,the baseline operating profile 600 can include a plurality of referencevalues 620 for the operating temperature T. More specifically, eachreference value of the plurality of reference values 620 can indicatethe operating temperature T during one of the plurality of flightphases. As shown, a first reference value 622 can indicate the operatingtemperature T during the takeoff phase of the test-flight(s). Inaddition, a second reference value 624 can indicate the operatingtemperature T during the climb phase of the test-flight(s).

Alternatively or additionally, the environmental parameter(s) caninclude a vibration measurement V_(M) from a sensor 450 configured tosense vibration of the electronic device 410. In example embodiments,the sensor 450 can be communicatively coupled to the communicationnetwork 230. In this way, the sensor 450 can transmit the vibrationmeasurement V_(M) to the computing device(s) 420 via the communicationnetwork 230. It should be appreciated that the sensor 450 can be anysuitable sensor configured to sense vibration of the electronic device410. For example, the sensor 450 can be an inertial measurement unit(IMU) that includes an accelerometer, a gyroscope, or both.

The vibration measurement V_(M) can vary amongst the plurality of flightphases of the test-flight(s). As such, the baseline operating profile600 can include a plurality of reference values 630 for the vibrationmeasurement V_(M). Each reference value of the plurality of referencevalues 630 can indicate the vibration measurement V_(M) taken during oneof the plurality of flight phases. As shown, a first reference value 632can indicate the vibration measurement V_(M) taken during the takeoffphase, whereas a second reference value 634 can indicate the vibrationmeasurement V_(M) taken during the climb phase.

The environmental parameter(s) can also include an amount of traffic(e.g., communications) on the communication network 230. The amount oftraffic on the communication network 230 can vary amongst the pluralityof phases of the test-flight(s). As such, the baseline operating profile600 can include a plurality of reference values 640 indicative of theamount of traffic on the communication network 230. Each reference valueof the plurality of reference values 640 can indicate an amount oftraffic on the communication network 230 during one of the plurality offlight phases. As shown, a first reference value 642 can indicate theamount of traffic on the communication network 230 during the takeoffphase, whereas a second reference value 644 can indicate the amount oftraffic on the communication network during the climb phase.

The computing device(s) 420 can be further configured to monitorcommunications on the communication network 230 during a post-validationperiod that follows the validation period. The post-validation can spanone or more flight(s) of the aerial vehicle 100, and the flight(s) caninclude a plurality of flight phases. For example, the plurality offlight phases can include, without limitation, a standing at gate phase,a taxiing phase, a takeoff phase, a climb phase, a cruise phase, anapproach phase and a landing phase. As will be discussed below in moredetail, the computing device(s) 420 can generate a present operatingprofile 700 (FIG. 7) of the electronic device 410 based, at least inpart, on communications monitored during the post-validation period.

When monitoring communications during the post-validation period, thecomputing device(s) 420 can listen for communications involving theelectronic device 410. In this way, the computing device(s) 420 candetermine how frequently another electronic device on the network 230communicates with the electronic device 410. Alternatively oradditionally, the computing device(s) 420 can determine the content ofcommunications involving the electronic device 410. More specifically,the content can include, without limitation, one or more parametersassociated with data packets transmitted or received by the electronicdevice 410.

In example embodiments, the computing device(s) 420 can detecttransmission of both a third data packet and a fourth data packet duringthe post-validation period. The third data packet can be from anotherelectronic device on the network 230 and intended for the electronicdevice 410, whereas the fourth data packet can be indicative of theelectronic device 410 responding to the third data packet. The computingdevice(s) 420 can determine a time lapse from detecting transmission ofthe third data packet and detecting transmission of the fourth datapacket. In this way, the computing device(s) 420 can determine a presentresponse time of the electronic device 410.

In example embodiments, an amount of traffic on the communicationnetwork 230 can vary amongst the plurality of flight phases of theflight(s) occurring during the post-validation period. As such, thepresent operating profile 700 can include a second plurality of values710 for the present response time of the electronic device 410, and eachvalue of the second plurality of values 710 can indicate the presentresponse time during one of the flight phases. For example, a firstvalue 712 can indicate the present response time of the electronicdevice 410 during the takeoff phase of the flight(s) occurring duringthe post-validation period, whereas a second value 714 can indicate thepresent response time of the electronic device 410 during the climbphase of the flight(s) occurring during the post-validation period. Aswill be discussed below in more detail, the

The present operating profile 700 can also include actual values for theenvironmental parameter(s) detected during the post-validation period.As shown, the present operating profile 700 can include a plurality ofactual values 720 for the operating temperature T, a plurality of actualvalues 730 for the vibration measurement V_(M), and a plurality ofactual values 740 for the amount of traffic on the communication network230. More specifically, each value of the plurality of actual values 720for the operating temperature T can indicate an operating temperature ofthe electronic device 410 during one of the plurality of flight phasesof the flight(s) occurring during the post-validation period. Inaddition, each value of the plurality of actual values 730 for thevibration measurement V_(M) can indicate a vibration measurement V_(M)taken during one of the plurality of flight phases of the flight(s)occurring during the post-validation period. Still further, each valueof the plurality of actual values 740 can indicate the amount of trafficon the communication network 230 during one the plurality of flightphases of the flight(s) occurring during the post-validation period. Aswill be discussed below in more detail, the system 400 can be configuredto determine degradation in performance of the electronic device 410based, at least in part, on the baseline operating profile 600 and thepresent operating profile 700.

In example embodiments, the computing device(s) 420 can implement amodel 452 stored in memory 424 of the computing device(s) 420. The model452 can implement any suitable machine learning technique in order toclassify the present operating profile 700 of the electronic device 410as either a safe operating profile or an unsafe operating profile. Forexample, the model 452 can include a machine or statistical learningmodel structured as one of a linear discriminant analysis model, apartial least squares discriminant analysis model, a support vectormachine model, a random tree model, a logistic regression model, a naïveBayes model, a K-nearest neighbor model, a quadratic discriminantanalysis model, an anomaly detection model, a boosted and baggeddecision tree model, an artificial neural network model, a C4.5 model, ak-means model, or a combination of one or more of the foregoing. Inexample embodiments, the model 452 can be a neural network. However,other suitable types of machine or statistical learning models are alsocontemplated. It will also be appreciated that the model 452 can usecertain mathematical methods alone or in combination with one or moremachine or statistical learning models to classify the present operatingprofile 700 using a training set of data.

In example embodiment, the training set of data used to train the model452 can include the baseline operating profile 600 generated during thevalidation period. In this way, the computing device(s) 420 can, whenimplementing the model 452, compare the present operating profile 700against the baseline operating profile 600. More specifically, thecomputing device(s) 420 can be configured to compare the presentresponse time of the electronic device 410 against the baseline responsetime of the electronic device 410. For example, when the aerial vehicle100 is in the takeoff phase of the flight(s) occurring during thepost-validation period, the computing device(s) 420 can compare thefirst value 712 of the second plurality of values 710 (e.g., presentresponse time) against the first value 612 of the first plurality ofvalues 610 (e.g., baseline response time).

If, for example, the first value 712 indicative of the present responsetime during the takeoff phase falls outside the tolerance (e.g., windowof time) assigned to the first value 612 indicative of the baselineresponse time during the takeoff phase, the model 452 can determine thepresent operating profile 700 has deviated from the baseline operatingprofile 600. It should be appreciated that other data (e.g., actualvalues of environmental parameters) included in the present operatingprofile 700 can be compared against corresponding data (e.g., referencevalues of the environmental parameters) included in the baselineoperating profile 600 to improve overall accuracy of the model 452. Whenthe model 452 determines the present operating profile 700 has deviatedfrom the baseline operating profile 600, the model 452 can classify thepresent operating profile 700 as an unsafe operating profile. If,however, the first value 712 indicative of the present response timeduring the takeoff phase falls within the tolerance assigned to thefirst value 612 indicative of the baseline response time during thetakeoff phase, the model 452 can classify the present operating profile700 as a safe operating profile. As will be discussed below in moredetail, the model 452 can be further trained to classify the unsafeoperating profile as either a degraded operating profile or an unknownoperating profile.

In example embodiments, a training set of data can be used to train themodel 452 to classify unsafe operating profiles as either a degradedoperating profile or an unknown operating profile. More specifically,the training set of data can include one or more historical operatingprofiles of the electronic device 410 that were previously classified asdegraded operating profiles and uploaded to memory 424 of the computingdevice(s) 420. As will be discussed below in more detail, the historicaloperating profiles of the electronic device 410 can be updated overtime. In this way, the model 452 can compare the unsafe operatingprofile (e.g., present operating profile 700) against the one or morehistorical operating profiles to further classify the present operatingprofile 700 as either a degraded operating profile or an unknownoperating profile. If the unsafe operating profile (e.g., the presentoperating profile 700) corresponds to the one or more historicaloperating profiles, then the model 452 can classify the unsafe operatingprofile as a degraded operating profile. If, however, the unsafeoperating profile does not match the one or more historical operatingprofiles, then the model 452 can classify the unsafe operating profileas an unknown operating profile.

In one example embodiment, the degraded operating profile can indicatedegradation in the performance of the electronic device 410 due to thefailure of one or more local components (e.g., power supply) of theelectronic device 410. When the model 452 classifies the unsafeoperating profile (e.g., present operating profile 700) as a degradedprofile, the model 452 can estimate an amount of time remaining beforethe electronic device 410 becomes inoperable. In addition, the model 452can cause the computing device(s) 420 to automatically the schedule theaerial vehicle 100 for maintenance before the estimated amount of timeexpires. More specifically, the computing device(s) 42 can schedule theaerial vehicle 100 for maintenance at a time when the aerial vehicle isnot needed to transport passengers or cargo. In this way, the computingdevice(s) 420 can minimize downtime for the aerial vehicle 100, whichcan reduce or eliminate economic losses an owner (e.g., airliner)suffers when the aerial vehicle 100 is grounded for maintenance.

In one example embodiments, the unknown operating profile can indicatethat an unauthorized user (e.g., a hacker) has gained control of theelectronic device 410 via the communication network 230. When the model452 classifies the unsafe operating profile (e.g., present operatingprofile 700) as an unknown operating profile, the model 452 can cause,as will be discussed below in more detail, the computing device(s) 420to transmit the unknown operating profile to a remote computing device460 that is off board the aerial vehicle 100.

As shown, the computing device(s) 420 can be communicatively coupled tothe remote computing device 460 via any suitable wired or wirelesscommunications link. In example embodiments, the computing device(s) 420onboard the aerial vehicle 100 can transmit the present operatingprofile 700 to the remote computing device 460 each time the aerialvehicle 100 lands at an airport. More specifically, the computingdevice(s) 420 can transmit the present operating profile 700 to theremote computing device 460 once the aerial vehicle 100 docks at a gateof the airport. In some embodiments, the computing device(s) 420 cantransmit the most recent data packet (e.g., fourth data packet) thatelectronic device 410 transmitted just prior to the computing device(s)420 classifying the present operating profile 700 as an unknownoperating profile. In this way, the remote computing device 460 caninspect the contents of the most recent data packet.

As shown, the remote computing device 460 can include one or moreprocessor(s) 462 and one or more memory device(s) 464. The one or morememory device(s) 464 can store information accessible by the one or moreprocessor(s) 462, including computer-readable instructions that can beexecuted by the one or more processor(s) 462. The memory device(s) 464can further store data that can be accessed by the one or moreprocessor(s) 462. The remote computing device 460 can also include acommunication interface 466 used to communicate, for example, with theone or more computing device(s) 420. The hardware, implementation, andfunctionality of the components of the remote computing device 460 mayoperate, function, and include the same or similar components as thosedescribed with respect to the one or more computing device(s) 420.

The remote computing device 460 can also include a model 480 stored inthe memory device(s) 464. The model 480 can implement any suitablemachine learning technique. For example, the model 480 can include amachine or statistical learning model structured as one of a lineardiscriminant analysis model, a partial least squares discriminantanalysis model, a support vector machine model, a random tree model, alogistic regression model, a naïve Bayes model, a K-nearest neighbormodel, a quadratic discriminant analysis model, an anomaly detectionmodel, a boosted and bagged decision tree model, an artificial neuralnetwork model, a C4.5 model, a k-means model, or a combination of one ormore of the foregoing. In example embodiments, the model 480 can be aneural network. However, other suitable types of machine or statisticallearning models are also contemplated. It will also be appreciated thatthe model 480 can use certain mathematical methods alone or incombination with one or more machine or statistical learning models.

In example embodiments, the model 480 can be trained based on a set oftraining data that can include, for example, an operating profilespecific to each electronic device of a plurality of electronic devicesthat are identical to the electronic device 410 onboard the aerialvehicle 100. More specifically, each electronic device of the pluralityof electronic devices can be included onboard one aerial vehicle of afleet of aerial vehicles that, in some example embodiments, can beidentical to the aerial vehicle 100 discussed above with reference toFIGS. 1 and 2. In example embodiments, each electronic device can beconnected to a communication network onboard each aerial vehicle. Inaddition, the operating profile that is specific to each electronicdevice of the plurality of electronic devices can indicate performanceof the electronic device. As will be discussed below in more detail, themodel 480 can use the operating profile for each electronic device ofthe plurality of electronic devices to learn one or more patternsindicative of performance of the electronic device.

In example embodiments, the operating profile for each electronic deviceof the plurality of electronic devices can include data similar to thatincluded in the present operating profile 700 of the electronic device410 onboard the aerial vehicle 100. In particular, the operating profilefor each electronic device of the plurality of electronic devices caninclude data indicative of a present response time of the electronicdevice during each flight phase of the flight(s). In addition, theoperating profile for each electronic device can include actual valuesfor one or more environmental parameter(s) affecting operation of theelectronic device during each flight phase of the flight(s). In thisway, the model 480 can aggregate data included in the operating profilefor each electronic device of the plurality of electronic devices toidentify one or more patterns indicative of the performance of theplurality of electronic devices.

In example embodiments, one or more parameters (e.g., present responsetime, environmental parameters, etc.) of the unknown operating profilefor the electronic device 410 onboard the aerial vehicle 100 can becompared against corresponding parameters of the operating profile foreach electronic device of the plurality of electronic devices that areidentical to the electronic device 410. In this way, the model 480 candetermine whether the unknown operating profile (e.g., present operatingprofile 700) of the electronic device 410 should be classified as a safeoperating profile or an unsafe operating profile. If the model 480determines the unknown operating profile should be classified as anunsafe operating profile, the model 480 can compare the unknownoperating profile (e.g., present operating state 700) against one ormore degraded operating profiles the model 480 learned from aggregatingdata included in the operating profile for each electronic device of theplurality of electronic devices.

If the unknown operating profile (e.g., present operating profile 700)of the electronic device 410 corresponds to one of the degradedoperating profiles learned by the model 480, then the model 480 canclassify the unknown operating profile as a degraded operating profile.When the model 480 classifies the unknown operating profile as adegraded operating profile, the model 480 can use data from theoperating profile of each electronic device of the plurality ofelectronic devices to, if needed, adjust the estimated amount of timeremaining before the electronic device 410 becomes inoperable. If themodel 480 determines the estimated amount of time needs to be adjusted,the model 480 can cause the remote computing device 460 to adjust whenthe aerial vehicle 100 is scheduled for maintenance. More specifically,the remote computing device 460 can transmit a command to the computingdevice(s) 420 onboard the aerial vehicle 100. The command can cause thecomputing device(s) 420 to reschedule a maintenance appointmentpreviously made for the aerial vehicle 100. In this way, the model 480can be used to more accurately predict the amount of time remainingbefore the electronic device 410 becomes inoperable.

If, however, the unknown operating profile (e.g., present operatingprofile) of the electronic device 410 does not correspond to one of thedegraded profiles learned by the model 480, then the model 480 cancompare the unsafe operating profile of the electronic device 410against one or more historical operating profiles that have each beenclassified as an attack profile. In example embodiments, the attackprofile can indicate that the electronic device 410 is executing amalicious program (e.g., malware) uploaded to the memory 424 of theelectronic device 410. It should be appreciated that the historicaloperating profiles can be determined based, at least in part, on datafrom the operating profile for each electronic device of the pluralityof electronic devices that are identical to the electronic device 410.If the unknown operating profile of the electronic device 410 does notmatch one of the historical operating profiles already included in themodel 480, then the unknown operating profile can be added to thehistorical operating profiles included in the model 480. In addition,the model 480 can cause the remote computing device 460 to generate anotification of the unknown operating profile. More specifically, thenotification can be an e-mail or any other suitable electronic messageviewable by authorized personnel. In this way, authorized personnel canperform forensic analysis on the electronic device 410 onboard theaerial vehicle 100 and develop a patch (e.g., software or hardware) forthe attack profile. In example embodiments, the patch can be pushed toeach electronic device of the plurality of electronic devices.

In example embodiments, the degraded operating profiles learned by themodel 480 executed by the remote computing device 480 can be uploaded tothe computing device(s) 420 onboard the aerial vehicle 100. Morespecifically, the degraded operating profiles can be uploaded to the oneor more historical operating profiles included in the model 452 executedby the computing device(s) 420. In this way, the accuracy of the model452 executed by the computing device(s) 420 onboard each aerial vehiclecan be improved.

In alternative embodiments, the model 452 implemented by the computingdevice(s) 420 onboard the aerial vehicle 100 can classify an unsafeoperating profile of the electronic device 410 as one of a degradedoperating profile, an attack profile, or an unknown operating profile.It should be appreciated that the model 452 can classify the unsafeoperating profile as the degraded operating profile in the same manneras discussed above. In addition, the one or more historical operatingprofiles included in the model 480 implemented by the remote computingdevice 460 can be uploaded to the model 452 implemented by the computingdevice(s) 420 onboard the aerial vehicle. In this way the model 452 canclassify compare the unsafe operating profile against the one or morehistorical operating profiles that have previously been classified asattack profiles. If the unsafe operating profile of the electronicdevice 410 corresponds to one of the historical operating profilesclassified as an attack profile, then the model 452 can classify theunsafe operating profile as an attack profile and take the appropriateaction. If, however, the unsafe operating profile of the electronicdevice 410 cannot be classified as an attack profile, then the model 452can classify the unsafe operating profile as an unknown operatingprofile and transmit the unknown operating profile to the remotecomputing device 460.

FIG. 8 another example embodiment of a system 800 for monitoringoperation of the electronic device 410 connected to the communicationnetwork 230 for the aerial vehicle 100. The system 800 depicted in FIG.8 may be configured in substantially the same manner as the system 400depicted in FIG. 4, and accordingly, the same or similar referencenumbers may refer to the same or similar parts. For example, the system800 can include the computing device(s) 420 discussed above withreference to the system 400 of FIG. 4.

However, for the example embodiment depicted in FIG. 8, the system 800can also include a secondary device 840 configured to monitor one ormore signal(s) originating within the electronic device 410. Inparticular, the secondary device 840 can monitor discrete and/or analogsignals of one or more local components 842 of the electronic device410. In example embodiments, the local component 842 can include,without limitation, an actuator or one or more computing device(s) ofthe electronic device 410. In addition, the secondary device 840 canmonitor discrete and/or analog signals transmitted from or received bythe local component 842. In this way, the secondary device 840 canmonitor operation of the local component 842. The secondary device 840can provide local data (e.g. discrete and/or analog signals) to thecomputing device(s) 420. In this way, the remote computing device 460can use the local data to improve the accuracy of the model 452. As willbe discussed below in more detail, the local data can be used todistinguish attacks by unauthorized attacks from normal degradation ofthe electronic device 410.

In example embodiments, the local data can indicate that the computingdevice(s) of the electronic device 410 are dropping data packets. Morespecifically, the computing device(s) may be ignoring one or morecommands received from another electronic device on the communicationnetwork 230. The computing device(s) 420 or the remote computing device460 can correlate the local data with data indicative of the flightphase and one or more environmental parameter(s) to determine a cause ofthe electronic device, specifically the computing device(s) thereof,dropping data packets. In one example embodiment, the computingdevice(s) 420 can determine the cause is an unauthorized user gainingaccess to the electronic device 410. Alternatively, the computingdevice(s) 420 can determine the cause is degradation of the computingdevice(s) included in the electronic device 410.

FIG. 9 depicts a flow diagram of an example method 900 for determiningdegradation in performance of an electronic device connected to acommunication network for an aerial vehicle. The method 900 can beimplemented using, for instance, the systems 400, 800 of FIGS. 4 and 8.FIG. 9 depicts steps performed in a particular order for purposes ofillustration and discussion. Those of ordinary skill in the art, usingthe disclosures provided herein, will understand that various steps ofany of the methods disclosed herein can be adapted, modified,rearranged, performed simultaneously or modified in various ways withoutdeviating from the scope of the present disclosure.

At (902), the method 900 can include monitoring, by one or morecomputing devices, communications on the communication network during avalidation period. Specifically, in example embodiments, the validationperiod can include one or more test-flight(s) of the aerial vehicle. Thetest-flight(s) can include a plurality of flight phases such as, withoutlimitation, a takeoff phase, a climb phase, a cruise phase, a descentphase, and a landing phase.

At (904), the method 900 can include generating, by the one or morecomputing device(s), a baseline operating profile of the electronicdevice based, at least in part, on the communications monitored duringthe validation period. Specifically, in example embodiments, thebaseline operating profile can include a first plurality of values. Inparticular, each value of the first plurality of values can indicate abaseline response time of the electronic device during one flight phaseof the test-flight(s) occurring during the validation period. Inaddition, the baseline operating profile can include a plurality ofreference values for one or more environmental parameter(s). Morespecifically, each value of the plurality reference values can indicatea value of the environmental parameter(s) during one flight phase of thetest-flight(s).

At (906), the method 900 can include monitoring, by one or morecomputing devices, communications on the communication network during apost-validation period. Specifically, in example embodiments, thepost-validation period can include one or more flight(s) of the aerialvehicle. The flight(s) can include a plurality of flight phases such as,without limitation, a takeoff phase, a climb phase, a cruise phase, adescent phase, and a landing phase.

At (908), the method 900 can include generating, by the one or morecomputing devices, a present operating profile of the electronic devicebased, at least in part, on communications monitored during thepost-validation period. Specifically, in example embodiments, thepresent operating profile can include a second plurality of values. Inparticular, each value of the second plurality of values can indicate apresent response time of the electronic device during one flight phaseof the flight(s) occurring during the post-validation period. Inaddition, the present operating profile can include a plurality ofreference values for one or more environmental parameter(s). Morespecifically, each value of the plurality reference values can indicatea value of the environmental parameter(s) during one flight phase of theflight(s) occurring during the post-validation period.

At (910), the method 900 can include determining, by the one or morecomputing devices, degradation in performance of the electronic devicewhen the present operating profile generated at (908) deviates from thebaseline operating profile generated at (904). Specifically, in exampleembodiments, a first value of the second plurality of values determinedat (908) can be compared against a first value of the first plurality ofvalues determined at (904). When the first value of the second pluralityof values falls outside a tolerance determined for the first value ofthe first plurality of values, the one or more computing devices candetermine the performance of the electronic device has degraded. Incontrast, when the first value of the second plurality of values fallswithin the tolerance determined for the first value of the firstplurality of values, the one or more computing devices can determine theperformance of the electronic device has not degraded.

If, at (910), the one or more computing devices determine theperformance of the electronic device has degraded, the method 900 caninclude, at (912), generating, by the one or more computing devices, anotification indicating the degradation in the performance of theelectronic device. Specifically, in example embodiments, thenotification can be displayed on a flight display of the aerial vehicle.Alternatively or additionally, the notification can be displayed on afeedback device viewable by personnel authorized to schedule the aerialvehicle 100 for maintenance.

In some embodiments, the method 900 can include automaticallyscheduling, by the one or more computing devices, the aerial vehicle formaintenance. In this way, the aerial vehicle can be scheduled formaintenance at a time that minimizes costs to an owner or operator ofthe aerial vehicle.

The technology discussed herein makes reference to computer-basedsystems and actions taken by and information sent to and fromcomputer-based systems. One of ordinary skill in the art will recognizethat the inherent flexibility of computer-based systems allows for agreat variety of possible configurations, combinations, and divisions oftasks and functionality between and among components. For instance,processes discussed herein can be implemented using a single computingdevice or multiple computing devices working in combination. Databases,memory, instructions, and applications can be implemented on a singlesystem or distributed across multiple systems. Distributed componentscan operate sequentially or in parallel.

This written description uses examples to disclose example embodimentsof the present disclosure, including making and using any devices orsystems and performing any incorporated methods. The patentable scope ofthe present disclosure is defined by the claims, and may include otherexamples that occur to those skilled in the art. Such other examples areintended to be within the scope of the claims if they include structuralelements that do not differ from the literal language of the claims, orif they include equivalent structural elements with insubstantialdifferences from the literal languages of the claims.

What is claimed is:
 1. A method for determining degradation inperformance of an electronic device connected to a communication networkfor an aerial vehicle, the method comprising: monitoring, by one or morecomputing devices, communications on the communication network during avalidation period; generating, by the one or more computing devices, abaseline operating profile of the electronic device based, at least inpart, on the communications monitored during the validation period;monitoring, by the one or more computing devices, communications on thecommunication network during a post-validation period; generating, bythe one or more computing devices, a present operating profile of theelectronic device based, at least in part, on the communicationsmonitored during the post-validation period; determining, by the one ormore computing devices, degradation in performance of the electronicdevice when the present operating profile deviates from the baselineoperating profile; and generating, by the one or more computing devices,a notification indicating the degradation in the performance of theelectronic device.
 2. The method of claim 1, wherein the validationperiod spans one or more test-flights of the aerial vehicle, wherein thepost-validation period spans one or more flights of the aerial vehicle,and wherein both the one or more test-flights occurring during thevalidation period and the one or more flights occurring during thepost-validation period each include a plurality of flight phases.
 3. Themethod of claim 2, wherein monitoring communication on the communicationnetwork during both the validation period and the post-validation periodcomprises receiving, at the one or more computing devices, data signalsfrom a secondary device associated with the electronic device, thesecondary device configured to monitor operation of one or more localcomponents of the electronic device.
 4. The method of claim 2, whereinmonitoring communications on the communication network during both thevalidation period and the post-validation period comprises receiving, atthe one or more computing devices, one or more environmental parametersaffecting operation of the electronic device.
 5. The method of claim 4,wherein the one or more environmental parameters comprise at least oneof an operating temperature of the first electronic device, a vibrationmeasurement indicative of vibration of the electronic device, and anamount of traffic on the communication network.
 6. The method of claim5, wherein monitoring communications on the communication network duringthe validation period comprises: detecting, by the one or more computingdevices, transmission of a first data packet to the electronic device;detecting, by the one or more computing devices, transmission of asecond data packet from the electronic device, the second data packetresponsive to the first data packet; and determining, by the one or morecomputing devices, a baseline response time of the electronic device,the baseline response time equal to a lapse of time from detectingtransmission of the first data packet to detecting transmission of thesecond data packet.
 7. The method of claim 6, wherein detectingtransmission of the first data packet comprises detecting, by the one ormore computing devices, transmission of the first data packet to theelectronic device during each flight phase of the one or moretest-flights, wherein detecting transmission of the second data packetcomprises detecting, by the one or more computing devices, transmissionof the second data packet from the electronic device during each flightphase of the one or more test-flights, wherein determining the baselineresponse time of the electronic device comprises determining, by thecomputing devices, a first plurality of values, and wherein each valueof the first plurality of values is indicative of the baseline responsetime during one flight phase of the one or more test-flights.
 8. Themethod of claim 7, further comprising determining, by the one or morecomputing devices, a tolerance for each value of the first plurality ofvalues, the tolerance based, at least in part, on the one or moreenvironmental parameters.
 9. The method of claim 8, wherein the baselineoperating profile comprises the first plurality of values and thetolerance determined for each value of the first plurality of values.10. The method of claim 9, wherein monitoring communications on thecommunication network during the post-validation period comprises:detecting, by the one or more computing devices, transmission of a thirddata packet to the electronic device; detecting, by the one or morecomputing devices, transmission of a fourth data packet from theelectronic device, the fourth data packet responsive to the third datapacket; and determining, by the one or more computing devices, a presentresponse time of the electronic device, wherein the present responsetime is equal to a lapse of time from detecting transmission of thethird data packet to detecting transmission of the fourth data packet.11. The method of claim 10, wherein transmission of the third datapacket occurs during each flight phase of the one or more flightsoccurring during the post-validation period, wherein detectingtransmission of the fourth data packet occurs during each flight phaseof the one or flights occurring during the post-validation period,wherein determining the present response time of the electronic devicecomprises determining, by the one or more computing devices, a secondplurality of values, and wherein each value of the second plurality ofvalues is indicative of the present response time of the electronicdevice during one flight phase of the one or more flights occurringduring the post-validation period.
 12. The method of claim 11, whereinthe present operating profile comprises the second plurality of valuesand a plurality of actual values for the one or more environmentalparameters, and wherein each value of the plurality of actual valuesindicates a value of the one or more environmental parameters during oneflight phase of the one or more flights occurring during thepost-validation period.
 13. The method of claim 11, wherein determiningdegradation in the performance of the electronic device comprises:comparing, by the one or more computing devices, the present responsetime of the electronic device against the baseline response time of theelectronic device; and determining, by the one or more computingdevices, degradation in the performance of the electronic device whenthe present response time deviates from the baseline response time by apredetermined amount.
 14. The method of claim 13, wherein comparing thepresent response time against the baseline response time comprisescomparing, by the one or more computing devices, a first value of thefirst plurality of values against a first value of the second pluralityof values, wherein the first value of the first plurality of values isindicative of the baseline response time during a first flight phase,and wherein the first value of the second plurality of values isindicative of the present response time during the first flight phase.15. The method of claim 1, wherein the one or more computing device areonboard the aerial vehicle, and wherein determining the presentoperating profile deviates from the baseline profile comprises:classifying, by the one or more computing devices, the present operatingprofile of the electronic device as an unsafe operating profile; andwhen the present operating profile is classified as the unsafe operatingprofile, classifying, by the one or more computing devices, the unsafeoperating profile as either a degraded operating profile or an unknownoperating profile, wherein the computing device(s) are configured toclassify the present operating profile as the unsafe operating profilebased on a model implemented by the computing device(s), and wherein thecomputing device(s) are configured to classify the unsafe operatingprofile as either the degraded operating or the unknown profile based,at least in part, on the model.
 16. The method of claim 15, wherein whenthe present operating is classified as the unknown operating profile,determining the present operating profile deviates from the baselineoperating profile further includes: transmitting, by the computingdevice(s), the present operating profile to a remote computing device;and updating, by the remote computing device, the model implemented bythe computing device(s) onboard the aerial vehicle based, at least inpart, on a model implemented by the remote computing device, wherein themodel implemented by the remote computing device is trained, at least inpart, on data from a plurality of electronic devices that are identicalto the electronic onboard the aerial vehicle.
 17. The method of claim16, wherein both the model implemented by the computing device(s) andthe model implemented by the remote computing device is a machine orstatistical learning model structured as one of a linear discriminantanalysis model, a partial least squares discriminant analysis model, asupport vector machine model, a random tree model, a logistic regressionmodel, a naïve Bayes model, a K-nearest neighbor model, a quadraticdiscriminant analysis model, an anomaly detection model, a boosted andbagged decision tree model, an artificial neural network model, a C4.5model and a k-means model.
 18. A system for determining degradation inperformance of an electronic device connected to a communication networkfor an aerial vehicle, the system comprising: one or more computingdevices connected to the communication network, the one or morecomputing devices comprising one or more processors and one or morememory devices, the one or more memory storing instructions that whenexecuted by the one or more processors cause the one or more processorsto perform operations, the one or more computing devices configured to:monitor communications on the communication network during a validationperiod; generate a baseline operating profile of the electronic devicebased, at least in part, on the communications monitored during thevalidation period; monitor communications on the communication networkduring a post-validation period; generate a present operating profile ofthe electronic device based, at least in part, on the communicationsmonitored during the post-validation period; determine degradation inperformance of the electronic device when the present operating profiledeviates from the baseline operating profile; and automatically schedulethe aerial vehicle for maintenance when the present operating profiledeviates from the baseline operating profile.
 19. The system of claim18, wherein the validation period spans one or more test-flights of theaerial vehicle, wherein the post-validation period spans one or moreflights of the aerial vehicle, and wherein both the one or moretest-flights occurring during the validation period and the one or moreflights occurring during the post-validation period each include aplurality of flight phases.
 20. The system of claim 18, wherein the oneor more computing devices are further configured to receive one or moreenvironmental parameters indicative of operation of the electronicdevice, wherein the one or more computing devices are configured toreceive the one or more environmental parameters during both thevalidation period and the post-validation period.